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ControlNet-v1-1-Annotators-cpu
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atatakun commited on
Commit
9ae92d6
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1 Parent(s): 8db5b12

Update app.py

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Files changed (1) hide show
  1. app.py +30 -15
app.py CHANGED
@@ -245,7 +245,8 @@ with block:
245
  gr.Markdown("## Canny Edge")
246
  with gr.Row():
247
  with gr.Column():
248
- input_image = gr.Image(source='upload', type="numpy")
 
249
  low_threshold = gr.Slider(label="low_threshold", minimum=1, maximum=255, value=100, step=1)
250
  high_threshold = gr.Slider(label="high_threshold", minimum=1, maximum=255, value=200, step=1)
251
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
@@ -260,7 +261,8 @@ with block:
260
  gr.Markdown("## HED Edge "SoftEdge"")
261
  with gr.Row():
262
  with gr.Column():
263
- input_image = gr.Image(source='upload', type="numpy")
 
264
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
265
  run_button = gr.Button(label="Run")
266
  with gr.Column():
@@ -273,7 +275,8 @@ with block:
273
  gr.Markdown("## Pidi Edge "SoftEdge"")
274
  with gr.Row():
275
  with gr.Column():
276
- input_image = gr.Image(source='upload', type="numpy")
 
277
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
278
  run_button = gr.Button(label="Run")
279
  with gr.Column():
@@ -286,7 +289,8 @@ with block:
286
  gr.Markdown("## MLSD Edge")
287
  with gr.Row():
288
  with gr.Column():
289
- input_image = gr.Image(source='upload', type="numpy")
 
290
  value_threshold = gr.Slider(label="value_threshold", minimum=0.01, maximum=2.0, value=0.1, step=0.01)
291
  distance_threshold = gr.Slider(label="distance_threshold", minimum=0.01, maximum=20.0, value=0.1, step=0.01)
292
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64)
@@ -301,7 +305,8 @@ with block:
301
  gr.Markdown("## MIDAS Depth")
302
  with gr.Row():
303
  with gr.Column():
304
- input_image = gr.Image(source='upload', type="numpy")
 
305
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64)
306
  run_button = gr.Button(label="Run")
307
  with gr.Column():
@@ -315,7 +320,8 @@ with block:
315
  gr.Markdown("## Zoe Depth")
316
  with gr.Row():
317
  with gr.Column():
318
- input_image = gr.Image(source='upload', type="numpy")
 
319
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
320
  run_button = gr.Button(label="Run")
321
  with gr.Column():
@@ -328,7 +334,8 @@ with block:
328
  gr.Markdown("## Normal Bae")
329
  with gr.Row():
330
  with gr.Column():
331
- input_image = gr.Image(source='upload', type="numpy")
 
332
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
333
  run_button = gr.Button(label="Run")
334
  with gr.Column():
@@ -341,7 +348,8 @@ with block:
341
  gr.Markdown("## DWPose")
342
  with gr.Row():
343
  with gr.Column():
344
- input_image = gr.Image(source='upload', type="numpy")
 
345
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
346
  run_button = gr.Button(label="Run")
347
  with gr.Column():
@@ -354,7 +362,8 @@ with block:
354
  gr.Markdown("## Openpose")
355
  with gr.Row():
356
  with gr.Column():
357
- input_image = gr.Image(source='upload', type="numpy")
 
358
  hand_and_face = gr.Checkbox(label='Hand and Face', value=False)
359
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
360
  run_button = gr.Button(label="Run")
@@ -368,7 +377,8 @@ with block:
368
  gr.Markdown("## Lineart Anime \n<p>Check Invert to use with Mochi Diffusion.")
369
  with gr.Row():
370
  with gr.Column():
371
- input_image = gr.Image(source='upload', type="numpy")
 
372
  invert = gr.Checkbox(label='Invert', value=True)
373
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
374
  run_button = gr.Button(label="Run")
@@ -382,7 +392,8 @@ with block:
382
  gr.Markdown("## Lineart \n<p>Check Invert to use with Mochi Diffusion. Inverted image can also be created here for use with ControlNet Scribble.")
383
  with gr.Row():
384
  with gr.Column():
385
- input_image = gr.Image(source='upload', type="numpy")
 
386
  coarse = gr.Checkbox(label='Using coarse model', value=False)
387
  invert = gr.Checkbox(label='Invert', value=True)
388
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
@@ -422,7 +433,8 @@ with block:
422
  gr.Markdown("## Oneformer COCO Segmentation")
423
  with gr.Row():
424
  with gr.Column():
425
- input_image = gr.Image(source='upload', type="numpy")
 
426
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
427
  run_button = gr.Button(label="Run")
428
  with gr.Column():
@@ -435,7 +447,8 @@ with block:
435
  gr.Markdown("## Oneformer ADE20K Segmentation")
436
  with gr.Row():
437
  with gr.Column():
438
- input_image = gr.Image(source='upload', type="numpy")
 
439
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=640, step=64)
440
  run_button = gr.Button(label="Run")
441
  with gr.Column():
@@ -448,7 +461,8 @@ with block:
448
  gr.Markdown("## Content Shuffle")
449
  with gr.Row():
450
  with gr.Column():
451
- input_image = gr.Image(source='upload', type="numpy")
 
452
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
453
  run_button = gr.Button(label="Run")
454
  with gr.Column():
@@ -461,7 +475,8 @@ with block:
461
  gr.Markdown("## Color Shuffle")
462
  with gr.Row():
463
  with gr.Column():
464
- input_image = gr.Image(source='upload', type="numpy")
 
465
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
466
  run_button = gr.Button(label="Run")
467
  with gr.Column():
 
245
  gr.Markdown("## Canny Edge")
246
  with gr.Row():
247
  with gr.Column():
248
+ # input_image = gr.Image(source='upload', type="numpy")
249
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
250
  low_threshold = gr.Slider(label="low_threshold", minimum=1, maximum=255, value=100, step=1)
251
  high_threshold = gr.Slider(label="high_threshold", minimum=1, maximum=255, value=200, step=1)
252
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
 
261
  gr.Markdown("## HED Edge&nbsp;&quot;SoftEdge&quot;")
262
  with gr.Row():
263
  with gr.Column():
264
+ # input_image = gr.Image(source='upload', type="numpy")
265
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
266
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
267
  run_button = gr.Button(label="Run")
268
  with gr.Column():
 
275
  gr.Markdown("## Pidi Edge&nbsp;&quot;SoftEdge&quot;")
276
  with gr.Row():
277
  with gr.Column():
278
+ # input_image = gr.Image(source='upload', type="numpy")
279
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
280
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
281
  run_button = gr.Button(label="Run")
282
  with gr.Column():
 
289
  gr.Markdown("## MLSD Edge")
290
  with gr.Row():
291
  with gr.Column():
292
+ # input_image = gr.Image(source='upload', type="numpy")
293
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
294
  value_threshold = gr.Slider(label="value_threshold", minimum=0.01, maximum=2.0, value=0.1, step=0.01)
295
  distance_threshold = gr.Slider(label="distance_threshold", minimum=0.01, maximum=20.0, value=0.1, step=0.01)
296
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64)
 
305
  gr.Markdown("## MIDAS Depth")
306
  with gr.Row():
307
  with gr.Column():
308
+ # input_image = gr.Image(source='upload', type="numpy")
309
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
310
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=384, step=64)
311
  run_button = gr.Button(label="Run")
312
  with gr.Column():
 
320
  gr.Markdown("## Zoe Depth")
321
  with gr.Row():
322
  with gr.Column():
323
+ # input_image = gr.Image(source='upload', type="numpy")
324
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
325
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
326
  run_button = gr.Button(label="Run")
327
  with gr.Column():
 
334
  gr.Markdown("## Normal Bae")
335
  with gr.Row():
336
  with gr.Column():
337
+ # input_image = gr.Image(source='upload', type="numpy")
338
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
339
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
340
  run_button = gr.Button(label="Run")
341
  with gr.Column():
 
348
  gr.Markdown("## DWPose")
349
  with gr.Row():
350
  with gr.Column():
351
+ # input_image = gr.Image(source='upload', type="numpy")
352
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
353
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
354
  run_button = gr.Button(label="Run")
355
  with gr.Column():
 
362
  gr.Markdown("## Openpose")
363
  with gr.Row():
364
  with gr.Column():
365
+ # input_image = gr.Image(source='upload', type="numpy")
366
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
367
  hand_and_face = gr.Checkbox(label='Hand and Face', value=False)
368
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
369
  run_button = gr.Button(label="Run")
 
377
  gr.Markdown("## Lineart Anime \n<p>Check Invert to use with Mochi Diffusion.")
378
  with gr.Row():
379
  with gr.Column():
380
+ # input_image = gr.Image(source='upload', type="numpy")
381
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
382
  invert = gr.Checkbox(label='Invert', value=True)
383
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
384
  run_button = gr.Button(label="Run")
 
392
  gr.Markdown("## Lineart \n<p>Check Invert to use with Mochi Diffusion. Inverted image can also be created here for use with ControlNet Scribble.")
393
  with gr.Row():
394
  with gr.Column():
395
+ # input_image = gr.Image(source='upload', type="numpy")
396
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
397
  coarse = gr.Checkbox(label='Using coarse model', value=False)
398
  invert = gr.Checkbox(label='Invert', value=True)
399
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
 
433
  gr.Markdown("## Oneformer COCO Segmentation")
434
  with gr.Row():
435
  with gr.Column():
436
+ # input_image = gr.Image(source='upload', type="numpy")
437
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
438
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
439
  run_button = gr.Button(label="Run")
440
  with gr.Column():
 
447
  gr.Markdown("## Oneformer ADE20K Segmentation")
448
  with gr.Row():
449
  with gr.Column():
450
+ # input_image = gr.Image(source='upload', type="numpy")
451
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
452
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=640, step=64)
453
  run_button = gr.Button(label="Run")
454
  with gr.Column():
 
461
  gr.Markdown("## Content Shuffle")
462
  with gr.Row():
463
  with gr.Column():
464
+ # input_image = gr.Image(source='upload', type="numpy")
465
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
466
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
467
  run_button = gr.Button(label="Run")
468
  with gr.Column():
 
475
  gr.Markdown("## Color Shuffle")
476
  with gr.Row():
477
  with gr.Column():
478
+ # input_image = gr.Image(source='upload', type="numpy")
479
+ input_image = gr.Image(label="Input Image", type="numpy", height=512)
480
  resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
481
  run_button = gr.Button(label="Run")
482
  with gr.Column():